From 70eb569362caa88db7f41fa79cacef843b65cd60 Mon Sep 17 00:00:00 2001
From: "zhangkun9038@dingtalk.com" <zhangkun9038@dingtalk.com>
Date: Thu, 27 Nov 2025 12:37:44 +0800
Subject: [PATCH] =?UTF-8?q?=E6=8E=92=E6=9F=A5=E6=B2=A1=E6=9C=89n=E7=AC=94?=
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---
 freqtrade/templates/staticgrid.py | 47 ++++++++++++++++---------------
 1 file changed, 25 insertions(+), 22 deletions(-)

diff --git a/freqtrade/templates/staticgrid.py b/freqtrade/templates/staticgrid.py
index fc8e0396..238f7875 100644
--- a/freqtrade/templates/staticgrid.py
+++ b/freqtrade/templates/staticgrid.py
@@ -36,40 +36,43 @@ class StaticGrid(IStrategy):
 
     def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         """
-        Dynamic Grid Entry Logic:
-        - Automatically calculates grid levels based on current price
-        - Creates grid points with fixed percentage step (e.g., 1.5% apart)
-        - Works for any price range (BTC, ETH, SOL, etc.)
+        Static Grid Entry Logic:
+        - Buy at predefined grid levels: 1500, 1550, 1600, ..., 4500 (step 50)
+        - When price is at or below a grid level, produce buy signal
+        - Continuous buying at different grid levels as price moves
         """
         dataframe['enter_long'] = False
         
         if len(dataframe) == 0:
             return dataframe
         
-        # Get current price
         current_price = dataframe['close'].iloc[-1]
-        print(f"[StaticGrid] Current price: {current_price:.2f}", file=sys.stderr, flush=True)
+        current_low = dataframe['low'].iloc[-1]
+        print(f"[StaticGrid] Current price: {current_price:.2f}, low: {current_low:.2f}", file=sys.stderr, flush=True)
         
-        # Dynamic grid: use percentage-based steps instead of fixed price steps
-        # Grid step: 1.5% (you can adjust this)
-        grid_step_pct = 0.015  # 1.5%
+        # Define static grid levels
+        LOWER = 1500.0
+        UPPER = 4500.0
+        STEP = 50.0
         
-        # Create grid levels around current price
-        # Generate grid points below current price (for buying)
-        num_levels_below = 10  # Generate 10 levels below current price
+        # Generate all grid levels in the range
+        grid_levels = [LOWER + i * STEP for i in range(int((UPPER - LOWER) / STEP) + 1)]
         
-        for i in range(num_levels_below):
-            grid_price = current_price * ((1 - grid_step_pct) ** (i + 1))
-            
-            # Buy if price drops to or below this grid level
-            if dataframe['low'].iloc[-1] <= grid_price * 1.01:
+        entry_count = 0
+        
+        # For each grid level, check if price is at or below it
+        for grid_price in grid_levels:
+            # Buy if current low is at or below this grid level (with 0.5% tolerance)
+            if current_low <= grid_price * 1.005:
                 dataframe['enter_long'] = True
-                print(f"[StaticGrid] Buy signal at grid level {i+1}: {grid_price:.2f}", file=sys.stderr, flush=True)
-                break  # Only buy at one level per candle
+                entry_count += 1
+                if entry_count <= 5:  # Only print first 5 for brevity
+                    print(f"[StaticGrid] Entry at grid {grid_price:.0f}", file=sys.stderr, flush=True)
         
-        entries = dataframe['enter_long'].sum()
-        if entries > 0:
-            print(f"[StaticGrid] Entry signals: {entries}", file=sys.stderr, flush=True)
+        if entry_count > 5:
+            print(f"[StaticGrid] ... and {entry_count - 5} more grid levels", file=sys.stderr, flush=True)
+        
+        print(f"[StaticGrid] Total entry signals: {entry_count}", file=sys.stderr, flush=True)
         
         return dataframe